Dr. Sara Saeed Becomes the First Pakistani Female to Win Rolex Award

Pakistan is one of those countries that has got some amazing people who are working hard to make a name for themselves and their country. Women are also not behind in it and are making a name for themselves. One such woman that is making history is none other than Dr. Sara Saeed Khurram, the CEO, and co-founder of Sehat Kahaani. Recently she has been awarded the Rolex Award for her company in the category of Enterprise as Associate Laureate. This is the first time that a female has won the Rolex Awards for Pakistan as Sara became the first women to do so.

The Rolex Awards started back in 1976 in order to support extraordinary individuals aged between 18 – 30 years old. The projects selected of individuals were those that would help the world become a better place to live. And Sehat Kahaani surely promises that to the people of Pakistan. The startup aims to make it easier for everyone to have to access the doctor. The ambition is to make doctors available for every patient in Pakistan no matter in which area of the country they are, they should have access to doctors so that their basic problems can be cured.

The startup was founded by Dr. Sara Saeed along with Dr. Iffat Zafar Aga to utilize technology and provide digital healthcare facilities. The company Sehat Kahaani right now helps doctors to connect with patients in remote areas through e-health clinics. Another thing that Sehat Kahaani helps people with is to help people in urban areas connect with physicians through smartphones. This allows patients easy access to doctors online who can then have the whole history of the patient, chat history, and every other thing within the app of Sehat Kahaani only. The startup aims to connect doctors with every patient in Pakistan.

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Jennifer Mccarthy

Jennifer is Associate Professor (Ph.D) at Air University. Research Interests: Informatics; analysis of large-scale biological data sets (genomics, gene expression, proteolytic, networks); algorithms for integration of data from multiple data sources; visualization of biological data; machine learning methods in bio-informatics.

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